Neural Networks and Qualitative Physics
Neural Networks and Qualitative Physics
$72.99
USDThis book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems controlled by synaptic matrices, and set-valued analysis that plays a natural and crucial role in qualitative analysis and simulation. This allows many examples of neural networks to be presented in a unified way. In addition, several results on the control of linear and nonlinear systems are used to obtain a "learning algorithm" of pattern classification problems, such as the back-propagation formula, as well as learning algorithms of feedback regulation laws of solutions to control systems subject to state constraints.
- Well known author
Product details
August 2011Paperback
9781107402843
302 pages
229 × 152 × 16 mm
0.41kg
Available
Table of Contents
- 1. Neural networks: a control approach
- 2. Pseudo-inverses and tensor products
- 3. Associative memories
- 4. The gradient method
- 5. Nonlinear neural networks
- 6. External learning algorithm of feedback controls
- 7. Internal learning algorithm of feedback controls
- 8. Learning processes of cognitive systems
- 9. Qualitative analysis of static problems
- 10. Dynamical qualitative simulation.
